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DBMS > AllegroGraph vs. Badger vs. Datomic vs. Milvus

System Properties Comparison AllegroGraph vs. Badger vs. Datomic vs. Milvus

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Editorial information provided by DB-Engines
NameAllegroGraph  Xexclude from comparisonBadger  Xexclude from comparisonDatomic  Xexclude from comparisonMilvus  Xexclude from comparison
DescriptionHigh performance, persistent RDF store with additional support for Graph DBMSAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityA DBMS designed for efficient storage of vector data and vector similarity searches
Primary database modelDocument store infowith version 6.5
Graph DBMS
RDF store
Vector DBMS
Key-value storeRelational DBMSVector DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.16
Rank#179  Overall
#30  Document stores
#17  Graph DBMS
#7  RDF stores
#7  Vector DBMS
Score0.20
Rank#325  Overall
#49  Key-value stores
Score1.76
Rank#145  Overall
#66  Relational DBMS
Score1.81
Rank#144  Overall
#5  Vector DBMS
Websiteallegrograph.comgithub.com/­dgraph-io/­badgerwww.datomic.commilvus.io
Technical documentationfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmlgodoc.org/­github.com/­dgraph-io/­badgerdocs.datomic.commilvus.io/­docs/­overview.md
DeveloperFranz Inc.DGraph LabsCognitect
Initial release2004201720122019
Current release8.0, December 20231.0.6735, June 20232.3.4, January 2024
License infoCommercial or Open Sourcecommercial infoLimited community edition freeOpen Source infoApache 2.0commercial infolimited edition freeOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Zilliz Cloud – Cloud-native service for Milvus
Implementation languageGoJava, ClojureC++, Go
Server operating systemsLinux
OS X
Windows
BSD
Linux
OS X
Solaris
Windows
All OS with a Java VMLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Data schemeyes infoRDF schemasschema-freeyes
Typing infopredefined data types such as float or dateyesnoyesVector, Numeric and String
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.no infobulk load of XML files possiblenonono
Secondary indexesyesnoyesno
SQL infoSupport of SQLSPARQL is used as query languagenonono
APIs and other access methodsRESTful HTTP API
SPARQL
RESTful HTTP APIRESTful HTTP API
Supported programming languagesC#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala
GoClojure
Java
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyes infoJavaScript or Common Lispnoyes infoTransaction Functionsno
TriggersyesnoBy using transaction functionsno
Partitioning methods infoMethods for storing different data on different nodeswith Federationnonenone infoBut extensive use of caching in the application peersSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
nonenone infoBut extensive use of caching in the application peers
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationnoneImmediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes inforecommended only for testing and developmentyes
User concepts infoAccess controlUsers with fine-grained authorization concept, user roles and pluggable authenticationnonoRole based access control and fine grained access rights
More information provided by the system vendor
AllegroGraphBadgerDatomicMilvus
Specific characteristicsKnowledge Graph Platform Leader FedShard - Designed for Entity-Event Knowledge Graph...
» more
Milvus is an open-source and cloud-native vector database built for production-ready...
» more
Competitive advantagesAllegroGraph is uniquely suited to support adhoc queries through SPARQL, Prolog and...
» more
Highly available, versatile, and robust with millisecond latency. Supports batch...
» more
Typical application scenariosRAG: retrieval augmented generation Video media : video understanding, video deduplication....
» more
Key customersMilvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more
Market metricsAs of January 2024, 25k+ GitHub stars 10M+ downloads and installations​ ​ 3k+ enterprise...
» more
Licensing and pricing modelsMilvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
» more
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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